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Wavelet analysis to decompose a vibration simulation signal to improve pre-distribution testing of packaging

机译：小波分析分解振动模拟信号，以改善包装的预分布测试

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摘要

In general, vehicle vibration is non-stationary and has a non-Gaussian probability distribution; yet existing testing methods for packaging design employ Gaussian distributions to represent vibration induced by road profiles. This frequently results in over-testing and/or over-design of the packaging to meet a specification and correspondingly leads to wasteful packaging and product waste, which represent $15bn per year in the USA and €3bn per year in the EU. The purpose of the paper is to enable a measured non-stationary acceleration signal to be replaced by a constructed signal that includes as far as possible any non-stationary characteristics from the original signal. The constructed signal consists of a concatenation of decomposed shorter duration signals, each having its own kurtosis level. Wavelet analysis is used for the decomposition process into inner and outlier signal components. The constructed signal has a similar PSD to the original signal, without incurring excessive acceleration levels. This allows an improved and more representative simulated input signal to be generated that can be used on the current generation of shaker tables. The wavelet decomposition method is also demonstrated experimentally through two correlation studies. It is shown that significant improvements over current international standards for packaging testing are achievable; hence the potential for more efficient packaging system design is possible.
机译：通常，车辆振动是不稳定的，并且具有非高斯概率分布。然而，用于包装设计的现有测试方法采用高斯分布来表示道路轮廓引起的振动。这经常导致包装的过度测试和/或设计过度，以符合规格要求，并相应地导致浪费的包装和产品浪费，在美国，每年的花费为150亿美元，在欧盟为每年30亿欧元。本文的目的是使所测得的非平稳加速度信号能够被构造的信号代替，该构造信号包括尽可能多的与原始信号无关的非平稳特性。构造的信号由一系列分解的较短持续时间信号组成，每个信号都有自己的峰度水平。小波分析用于分解为内部和离群信号分量。所构建的信号具有与原始信号相似的PSD，而不会产生过多的加速度。这允许生成改进的且更具代表性的模拟输入信号，该输入信号可用于当前的振动台表。小波分解方法还通过两个相关研究进行了实验证明。结果表明，与当前的国际包装测试标准相比，可以实现重大改进；因此，有可能实现更高效的包装系统设计。

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